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Byron Boots
Byron Boots
Associate Professor, University of Washington
Email confirmado em cs.washington.edu - Página inicial
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Citado por
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Ano
One-shot learning for semantic segmentation
A Shaban, S Bansal, Z Liu, I Essa, B Boots
arXiv preprint arXiv:1709.03410, 2017
8432017
Information theoretic MPC for model-based reinforcement learning
G Williams, N Wagener, B Goldfain, P Drews, JM Rehg, B Boots, ...
2017 IEEE international conference on robotics and automation (ICRA), 1714-1721, 2017
6712017
Differentiable mpc for end-to-end planning and control
B Amos, I Jimenez, J Sacks, B Boots, JZ Kolter
Advances in neural information processing systems 31, 2018
4592018
Agile autonomous driving using end-to-end deep imitation learning
Y Pan, CA Cheng, K Saigol, K Lee, X Yan, E Theodorou, B Boots
arXiv preprint arXiv:1709.07174, 2017
3822017
Truncated back-propagation for bilevel optimization
A Shaban, CA Cheng, N Hatch, B Boots
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
2992019
Deeply aggrevated: Differentiable imitation learning for sequential prediction
W Sun, A Venkatraman, GJ Gordon, B Boots, JA Bagnell
International conference on machine learning, 3309-3318, 2017
2892017
Closing the learning-planning loop with predictive state representations
B Boots, SM Siddiqi, GJ Gordon
The International Journal of Robotics Research 30 (7), 954-966, 2011
2882011
Hilbert space embeddings of hidden Markov models
L Song, B Boots, S Siddiqi, G Gordon, A Smola
2492010
Continuous-time Gaussian process motion planning via probabilistic inference
M Mukadam, J Dong, X Yan, F Dellaert, B Boots
The International Journal of Robotics Research 37 (11), 1319-1340, 2018
2402018
Imitation learning for agile autonomous driving
Y Pan, CA Cheng, K Saigol, K Lee, X Yan, EA Theodorou, B Boots
The International Journal of Robotics Research 39 (2-3), 286-302, 2020
1752020
Gaussian process motion planning
M Mukadam, X Yan, B Boots
2016 IEEE international conference on robotics and automation (ICRA), 9-15, 2016
1692016
Motion planning as probabilistic inference using Gaussian processes and factor graphs.
J Dong, M Mukadam, F Dellaert, B Boots
Robotics: Science and Systems 12 (4), 10.15607, 2016
1642016
A constraint generation approach to learning stable linear dynamical systems
S Siddiqi, B Boots, G Gordon
CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF, 2008
158*2008
Learning from conditional distributions via dual embeddings
B Dai, N He, Y Pan, B Boots, L Song
Artificial Intelligence and Statistics, 1458-1467, 2017
1552017
Reduced-rank hidden Markov models
S Siddiqi, B Boots, G Gordon
Proceedings of the Thirteenth International Conference on Artificial …, 2010
1472010
4D crop monitoring: Spatio-temporal reconstruction for agriculture
J Dong, JG Burnham, B Boots, G Rains, F Dellaert
2017 IEEE International Conference on Robotics and Automation (ICRA), 3878-3885, 2017
1352017
Iris: Implicit reinforcement without interaction at scale for learning control from offline robot manipulation data
A Mandlekar, F Ramos, B Boots, S Savarese, L Fei-Fei, A Garg, D Fox
2020 IEEE International Conference on Robotics and Automation (ICRA), 4414-4420, 2020
1322020
Storm: An integrated framework for fast joint-space model-predictive control for reactive manipulation
M Bhardwaj, B Sundaralingam, A Mousavian, ND Ratliff, D Fox, F Ramos, ...
Conference on Robot Learning, 750-759, 2022
1292022
Hilbert space embeddings of predictive state representations
B Boots, G Gordon, A Gretton
arXiv preprint arXiv:1309.6819, 2013
1152013
Provably efficient imitation learning from observation alone
W Sun, A Vemula, B Boots, D Bagnell
International conference on machine learning, 6036-6045, 2019
1102019
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